High-performance computing (HPC) or supercomputer systems use specialized parallel computers and/or nodes to execute applications that require intensive computations, such as physical simulations, climate research, financial modeling, data mining, automotive design, and aerospace design. To run parallel applications efficiently, a supercomputer system needs network monitoring tools for monitoring and generating network data associated with the nodes of the supercomputer system, and data mapping tools that can map these applications to the computational nodes of the supercomputer system in such a way that minimizes cross-node communication while balancing their computational load within the supercomputer system. Various networking monitoring tools have been developed to generate network data that can be utilized by various data mapping tools of the supercomputer system.
A technical challenge within currently available network monitoring tools is that such network monitoring tools are not able to monitor network processes and traffic within the supercomputer system in real-time, and as a result these network monitoring tools are unable to provide continuous stream of monitored network data that can be used by topology-aware tools to map new applications to the supercomputer system in real-time.